Jinkyoo Park
Jinkyoo Park
Department of Industrial and Systems Engineering, KAIST
Verified email at kaist.ac.kr - Homepage
Cited by
Cited by
Layout optimization for maximizing wind farm power production using sequential convex programming
J Park, K Law
Applied Energy 151, 320-334, 2015
Electromagnetic energy harvester with repulsively stacked multilayer magnets for low frequency vibrations
SD Kwon, J Park, K Law
Smart materials and structures 22 (5), 055007, 2013
A data-driven, cooperative wind farm control to maximize the total power production
J Park, KH Law
Applied Energy 165, 151-165, 2016
Wind farm power maximization based on a cooperative static game approach
J Park, S Kwon, KH Law
Active and Passive Smart Structures and Integrated Systems 2013 8688, 86880R, 2013
Cooperative wind turbine control for maximizing wind farm power using sequential convex programming
J Park, KH Law
Energy Conversion and Management 101, 295-316, 2015
Large‐eddy simulation of stable boundary layer turbulence and estimation of associated wind turbine loads
J Park, S Basu, L Manuel
Wind Energy 17 (3), 359-384, 2014
An intelligent machine monitoring system for energy prediction using a Gaussian Process regression
R Bhinge, N Biswas, D Dornfeld, J Park, KH Law, M Helu, S Rachuri
2014 IEEE International Conference on Big Data (Big Data), 978-986, 2014
Toward a generalized energy prediction model for machine tools
R Bhinge, J Park, KH Law, DA Dornfeld, M Helu, S Rachuri
Journal of manufacturing science and engineering 139 (4), 2017
A generalized data-driven energy prediction model with uncertainty for a milling machine tool using Gaussian Process
J Park, KH Law, R Bhinge, N Biswas, A Srinivasan, DA Dornfeld, M Helu, ...
International Manufacturing Science and Engineering Conference 56833 …, 2015
Bayesian Ascent: A Data-Driven Optimization Scheme for Real-Time Control With Application to Wind Farm Power Maximization
J Park, KH Law
IEEE Transactions on Control Systems Technology,, 1-14, 2016
Classification of heart sound recordings using convolution neural network
H Ryu, J Park, H Shin
2016 Computing in Cardiology Conference (CinC), 1153-1156, 2016
Dissecting neural odes
S Massaroli, M Poli, J Park, A Yamashita, H Asama
arXiv preprint arXiv:2002.08071, 2020
Toward Isolation of Salient Features in Stable Boundary Layer Wind Fields that Influence Loads on Wind Turbines
J Park, L Manuel, S Basu
Energies 8 (4), 2977-3012, 2015
Physics-induced graph neural network: An application to wind-farm power estimation
J Park, J Park
Energy 187, 115883, 2019
Power evaluation of flutter-based electromagnetic energy harvesters using computational fluid dynamics simulations
J Park, G Morgenthal, K Kim, SD Kwon, KH Law
Journal of Intelligent Material Systems and Structures 25 (14), 1800-1812, 2014
An aero-elastic flutter based electromagnetic energy harvester with wind speed augmenting funnel
JK Park, KM Kim, SD Kwon, KH Law
Proceedings of the International Conference on Advances in Wind and …, 2012
A data-driven approach for cooperative wind farm control
J Park, SD Kwon, KH Law
2016 American Control Conference (ACC), 525-530, 2016
Gaussian process regression (GPR) representation in predictive model markup language (PMML)
J Park, D Lechevalier, R Ak, M Ferguson, KH Law, YTT Lee, S Rachuri
Smart and sustainable manufacturing systems 1 (1), 121, 2017
A Bayesian optimization approach for wind farm power maximization
J Park, KH Law
Smart Sensor Phenomena, Technology, Networks, and Systems Integration 2015 …, 2015
Stable neural flows
S Massaroli, M Poli, M Bin, J Park, A Yamashita, H Asama
arXiv preprint arXiv:2003.08063, 2020
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